1. Field of the Invention
The present invention relates to an evaluation of reliability of sample data to classify samples and quality control of sample data.
2. Description of the Related Art
In a polymorphic analysis of samples derived from a living body, the rate of progress of a polymorphic identification reaction is different from sample to sample depending on concentrations of the sample and presence/absence of inhibitors. Thus, polymorphic data having a wide distribution is obtained from polymorphic analysis.
Conventionally, the polymorphic analysis has been performed by using a statistical technique or genetic technique on signals of sample.
However, particularly for polymorphic analysis concerning genetic polymorphism, there are some kinds of polymorphism that are present only in several samples among several hundreds of samples, and thus statistics based on the conventional statistical technique may be meaningless.
Therefore, for polymorphic analysis concerning genetic polymorphism, reliability of polymorphic data obtained by the polymorphic analysis is generally evaluated genetic-statistically by using the Hardy-Weinberg equilibrium. Also, Kevin L Gunderson, Frank J Steemers, Grace Lee, Leo G Mendoza, and Mark S Chee, “A genome-wide scalable SNP genotyping assay using microarray technology”, NATURE GENETICS, VOLUME37, NUMBER 5, MAY, 2005 is disclosed as a technology to evaluate reliability of polymorphic data obtained by polymorphic analysis concerning genetic polymorphism. More specifically, the evaluation index “CSS” disclosed by Kevin L Gunderson, Frank J Steemers, Grace Lee, Leo G Mendoza, and Mark S Chee, “A genome-wide scalable SNP genotyping assay using microarray technology”, NATURE GENETICS, VOLUME37, NUMBER5, MAY, 2005, uses statistics for each cluster.
However, these conventional evaluation techniques assume that polymorphic data obtained from samples sampled from a group of random crossing is evaluated, and thus, for example, polymorphic data obtained from samples sampled only from specific samples such as family samples and patient samples are not appropriate for evaluation. If, for example, polymorphic data having only one genotype “BB” shown in FIG. 10 is selected for evaluation, no distribution/average corresponding to clusters of genotype “BB” is obtained, and thus it is difficult to calculate an evaluation value by the above conventional evaluation techniques.
That is, when a group is not obtained from random crossing or polymorphic data containing polymorphism whose frequency is small is obtained from polymorphic analysis concerning genetic polymorphism, it is difficult to evaluate reliability of such polymorphic data by the conventional evaluation technique.
Thus, conventionally, skilled operators have subjectively evaluated reliability of polymorphic data containing polymorphism whose frequency is small to extract error samples or decide the threshold of type classification.